Abstract:

Root system architecture (RSA) is the spatial distribution of roots of individual plants. As part of a collaborative effort I adapted a gellan gum based system for imaging and phenotyping of root systems in maize. This system was first used to perform a survey of 26 distinct maize varieties of the Nested Association Mapping (NAM) population. The analysis of these data showed a large amount of variation between different RSA, in particular demonstrating tradeoffs between architectures favoring sparse, but far reaching, root networks versus those favoring small but dense root networks. To study this further I imaged and phenotyped the B73 (compact) x Ki3 (exploratory) mapping population. These data were used to map 102 quantitative trait loci (QTL). A large portion of these QTL had large, ranging from 5.48% to 23.8%. Majority of these QTLs were grouped into 9 clusters across the genome, with each cluster favoring either the compact of exploratory RSA. In summary, our study demonstrates the power of the gellan based system to locate loci controlling root system architecture of maize, by combining rapid and highly detailed imaging techniques with semi-automated computation phenotyping.